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Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence (AI) will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of AI techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different AI techniques to be considered and then shows how these AI techniques are used for the components of IMS.

In the current competitive environment, each company faces a number of challenges: quick response to customers’ demands, high quality of products or services, customers’ satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data‐processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today’s manufacturing and service industries. In this paper, the authors propose a knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.

Steam turbine final assembly is a dynamic process, in which various interference events occur frequently. Currently, data transmission relies on oral presentation, while scheduling depends on the manual experience of managers. This mode has low information transmission efficiency and is difficult to timely respond to emergencies. Besides, it is difficult to consider various factors when manually adjusting the plan, which reduces assembly efficiency. The purpose of this paper is to propose a knowledge-based real-time scheduling system under cyber-physical system (CPS) environment which can improve the assembly efficiency of steam turbines.

First, an Internet of Things based CPS framework is proposed to achieve real-time monitoring of turbine assembly and improve the efficiency of information transmission. Second, a knowledge-based real-time scheduling system consisting of three modules is designed to replace manual experience for steam turbine assembly scheduling.

Experiments show that the scheduling results of the knowledge-based scheduling system outperform heuristic algorithms based on priority rules. Compared with manual scheduling, the delay time is reduced by 43.9%.

A knowledge-based real-time scheduling system under CPS environment is proposed to improve the assembly efficiency of steam turbines. This paper provides a reference paradigm for the application of the knowledge-based system and CPS in the assembly control of labor-intensive engineering-to-order products.

The integration of e‐business and supply chain enables seamless information flow from suppliers to customer service network via the internet. It also enables better‐coordinated materials flow from customer order to production, storage, distribution and delivery. The purpose of this paper is to describe the work that leads to the realisation of a hierarchical model for e‐supply chain coordination and optimisation.

The model is based on an e‐business information flow network in order to respond rapidly to the dynamics of e‐supply chain and market. It can be used to realize management level strategies, and facilitate the planning and control of detailed operation schedules of supply chain units in an e‐supply chain environment. Three main modules are discussed. They are routing and sequence optimiser (RSO) with the aid of a GA and TS‐based multiple population search strategy (MPSS); supply chain virtual clustering (SCVC) based on fuzzy virtual clustering; and supply chain order scheduling (SCOS) using an agent‐based distributed scheduling system.

These modules enable: the generation of preferred routings, transportation modes and work order plan under such constraints as customer service level, cycle time and cost; the formation of supply chain's unit‐transportation‐work order families using a clustering approach to down‐size supply chain problems and increase computation efficiency; and the integration of scheduling with supply chain optimisation in order to facilitate the control of a supply chain with the aid of an agent‐based distributed scheduling approach.

This paper proposed a hierarchical model for e‐supply chain coordination and optimisation that is capable to solve large‐scale problems. A MPSS using GA and TS was depicted in detail to expedite the RSO.

Scheduling needs to be concise and well‐determined but able to respond to the ever‐changing and uncertain market or environment against the constraints of production capacity, resources, time frame, etc. The purpose of this paper is to model and solve a scheduling problem with another domain perspective that adopts the concept of agent, and an agent‐based scheduling environment is proposed for solving the scheduling problem, in which three agents are developed, i.e. a sales agent, a scheduling agent, and a production agent.

The modeling and development of the proposed agent‐based scheduling environment and its agents under constraints are discussed. Constraint priority scheduling concepts are applied to the environment and its agents, and the feature of responding to customer change orders is included in the model. The proposed agent‐based scheduling environment with three agents is applied to a lamp‐manufacturing company in China as a case study, and the integrated agent‐based approach is also illustrated in the case study.

Throughout the autonomous communication between agents in the proposed model, a constraint‐prioritized schedule is generated to fulfill customer orders and customer change orders, as well as to achieve a better scheduling performance result. From the simulation results and analysis in the case study, satisfactory results show that the proposed model can generate a constraint‐prioritized schedule for the studied company that can completely fulfill customer orders, adjust and fulfill customer change orders, and achieve a better scheduling result.

In this paper, the scheduling problem is modeled and solved by using the domain perspective of agent‐based approach. By using an agent‐based approach, the agents can be implemented to represent manufacturing resources or aggregations of resources. Under the proposed modeling approach, the collaboration across the entire scheduling activities can be enhanced, and the efficiency and effectiveness in the scheduling activities can also be increased.

This paper aims to develop an algorithm to study the impact of dynamic resource disruption on project makespan and provide a suitable resource disruption ratio for various complex industrial and emergency projects.

This paper addresses the RCPSP in dynamic environments, which assumes resources will be disrupted randomly, that is, the information about resource disruption is not known in advance. To this end, a reactive scheduling model is proposed for the case of random dynamic disruptions of resources. To solve the reactive scheduling model, a hybrid genetic algorithm with a variable neighborhood search is proposed.

The results obtained on the PSLIB instances prove the performance advantage of the algorithm; through sensitivity analysis, it can be obtained, the project makespan increases exponentially as the number of disruptions increase. Furthermore, if more than 50% of the project's resources are randomly disrupted, the project makespan will be significantly impacted.

The paper focuses on the impact of dynamic resource disruptions on project makespan. Few studies have considered stochastic, dynamic resource uncertainty. In addition, this research proposes a reasonable scheduling algorithm for the research problem, and the conclusions drawn from the research provide decision support for project managers.

Several examples of successful expert systems applications are presented. Examples of expert systems as applied in process planning, operations planning, inventory control, process design, quality control and scheduling are covered, and the performance of these expert systems is described. Expert systems will become an essential part of computer‐integrated manufacturing (CIM) and flexible manufacturing systems (FMS) because they can perform several of the tasks mentioned above.

The interdisciplinary nature of video networking, coupled with various recent developments in standards, proposals and applications, poses great challenges to the research and industrial communities working in this area. The main purpose of this paper is to provide a tutorial and survey on recent advances in video networking from an integrated perspective of both video signal processing and networking.

Detailed technical descriptions and insightful analysis are presented for recent and emerging video coding standards, in particular the H.264 family. The applications of selected video coding standards in emerging wireless networks are then introduced with an emphasis on scalable video streaming in multihomed mobile networks. Both research challenges and potential solutions are discussed along the description, and numerical results through simulations or experiments are provided to reveal the performances of selected coding standards and networking algorithms.

The tutorial helps to clarify the similarities and differences among the considered standards and networking applications. A number of research trends and challenges are identified, and selected promising solutions are discussed. This practice would provoke further thoughts on the development of this area and open up more research and application opportunities.

Not all the concerned video coding standards are complemented with thorough studies of networking application scenarios.

The discussed video coding standards are either playing or going to play indispensable roles in the video industry; the introduced networking scenarios bring together these standards and various emerging wireless networking paradigms towards innovative application scenarios.

The comprehensive overview and critiques on existing standards and application approaches offer a valuable reference for researchers and system developers in related research and industrial communities.

This paper aims to propose a new concept of product manufacturing mode which takes physical manufacturing theory as the basic starting point. In this work, the authors intend to systematically define the basic connotation and extension of physical manufacturing, and sort out the typical characteristics of physical manufacturing, in order to propose the general concept of physical manufacturing.

How to study the combination of physics, mathematics, mechanics and other disciplines with the manufacturing disciplines, and how to elevate modern manufacturing science to a new height, has always been a problem for scientists in the field of manufacturing and engineering construction people to deeply think about. Therefore, on the basis of tracing the development of physics and combining the attributes and functions of manufacturing, the authors propose the basic concept of physical manufacturing. On this basis, the authors further clarify the connotation and extension, theoretical basis and technical system of physical manufacturing, reveal the basic problem domain of research and construct the theoretical foundation of physical manufacturing research, which are of great theoretical value and practical significance to adjust and optimize the manufacturing industry structure, improve the quality of manufacturing industry development and promote the green development of manufacturing industry.

The research on the basic theory and technical system of physical manufacturing will therefore broaden the way of thinking and make a better understanding of manufacturing science and technology, which will promote the development of manufacturing industry to some extent.

On the basis of continuous improvement of the basic theory and conceptual system of physical manufacturing, the physical manufacturing technology will become more and more perfect; physical manufacturing system and intelligent manufacturing system will become the mainstream of next-generation manufacturing system.

The purpose of this paper is to contribute to the extant literature about the exploitation of Internet of Things (IoT) in seaports by illustrating in detail how such IT infrastructures can impact on the redesign of their business processes. Thus, the research question of the study is: how do IoT technologies redesign the business processes of seaports?

The paper reports the illustrative case study of the German Port of Hamburg, one of the main European seaports, which widely adopted technologies based on IoT over the last few years.

The results show the adoption of IoT technologies widely redesigns and improves the performance of all the main business process of the port analyzed, in particular those processes related to technology and information of the organization. The IoT-driven business process redesign (BPR) must be planned strategically by the port management and implies the involvement of all the port stakeholders and, if necessary, the hiring external professional partners.

Despite some authors report generically which are the ports operational domains more affected by IoT, there is a lack of studies about the specific implications of the adoption of such technologies on the BPR of seaports. The paper fills in this gap.